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import os
import streamlit as st
import torch
from transformers import pipeline
import speech_recognition as sr
from gtts import gTTS
from io import BytesIO
from pydub import AudioSegment
import tempfile
# Set Hugging Face API key (replace 'your_hugging_face_api_key' with your actual API key)
os.environ["HUGGINGFACEHUB_API_TOKEN"] = "doctor app"
# Load the Hugging Face model for text generation
try:
chatbot = pipeline("text-generation", model="thrishala/mental_health_chatbot")
except Exception as e:
st.error(f"Error loading model: {e}")
# Function to capture voice input using SpeechRecognition and OpenAI Whisper
def get_voice_input():
recognizer = sr.Recognizer()
with sr.Microphone() as source:
st.write("Listening...")
audio = recognizer.listen(source)
st.write("Recognizing...")
try:
# Converting audio to text using OpenAI Whisper if available, fallback to Google's API otherwise
text = recognizer.recognize_google(audio)
return text
except sr.UnknownValueError:
st.error("Sorry, I could not understand the audio.")
return None
except sr.RequestError as e:
st.error(f"Could not request results; {e}")
return None
# Function to generate voice response using gTTS
def speak(text):
try:
tts = gTTS(text=text, lang='en')
audio_file = BytesIO()
tts.write_to_fp(audio_file)
audio_file.seek(0)
return audio_file
except Exception as e:
st.error(f"Error generating audio response: {e}")
return None
# Streamlit app layout
st.title("Mental Health Chatbot")
st.write("Talk to your mental health assistant!")
# Voice input button
if st.button("Speak"):
user_input = get_voice_input()
if user_input:
st.write(f"You: {user_input}")
# Get response from the chatbot
try:
response = chatbot(user_input, max_length=150, num_return_sequences=1)[0]['generated_text']
st.write(f"Bot: {response}")
# Generate voice response
audio_output = speak(response)
if audio_output:
st.audio(audio_output, format="audio/mp3")
except Exception as e:
st.error(f"Error generating response: {e}")
# Text input
user_input = st.text_input("Type your message:")
if st.button("Send"):
if user_input:
st.write(f"You: {user_input}")
# Get response from the chatbot
try:
response = chatbot(user_input, max_length=150, num_return_sequences=1)[0]['generated_text']
st.write(f"Bot: {response}")
# Generate voice response
audio_output = speak(response)
if audio_output:
st.audio(audio_output, format="audio/mp3")
except Exception as e:
st.error(f"Error generating response: {e}")
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